Questions:

  1. Explore the dataset. Consider plotting the number of types of opioids by state and number of opioid prescribers by state. Understand the most prevalent types of opioids prescribed. Explore the states with the highest prevalence of fatal opioid overdoses. How does this compare to total overdoses? Is there a correlation between type of opioids prescribed and overdose deaths? What patterns emerge? Use different types of plots to visualize your data (histogram, bee swarm, box plot, etc…).

  2. Test the assumption of the Pareto effect on opioid prescribing using the dataset (i.e., 20% of prescribers provide 80% of the opioids).

  3. Build a model to predict the number of fatal opioid overdoses. Consider building the model for a specific state, but that’s not necessary. Be creative-consider crossing the raw features that are available and creating new features (i.e., total type of opioids). Socioeconomics are often a driving factor for health outcomes. Can you find another dataset that provides information at the state level and can be used in your model? Can you perform tests to explain the variability in your outcome (i.e, effect estimation)?







Opioid deaths in 1999:

  • Overall Picture Good
  • New Mexico is the highest at 10 Deaths per 100,000







Opioid deaths in 2006:

  • Overall picture slightly worse than 1999, but still rate of overdose still relatively low
  • West Virginia had already taken off, with the highest death rate at 16 deaths per 100,000







Opioid deaths in 2016:

  • Overdoses have tripled in many states
  • West Virginia now at 43 deaths per 100,00
  • Most dramatic change in New England
    • New Hampshire went from 8 to 36 deaths per 100,000 from ’06 to ’16







Percent change in opioid deaths over the last two decades have been alarming

  • 10 states that with at least 1,000% increase in the rate of opioid deaths from ’99 to ’16







How does the prescribing rate compare to the death rate?

  • Starting in 2012, prescriptions in high-prescribing states began to decline
  • This leads to a clear divergence b/c deaths continue to not only increase after 2012, but also increase at a faster rate
  • This divergence happens b/c of increase of illegal opioid intake